Evidence map›Paper›PMID 40029604›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

3D-Printed Artificial Organ Models for Surgical Applications.

Chuchu Chen, Kaiyan Qiu

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Chuchu ChenSchool of Mechanical and Materials Engineering, Washington State University, Pullman, WA, USA.
Kaiyan QiuSchool of Mechanical and Materials Engineering, Washington State University, Pullman, WA, USA. kaiyan.qiu@wsu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical errors are one of the leading death causes in the United States, becoming a serious concern in clinical surgeries. Although full elimination of medical errors is unattainable, proper surgical planning and rehearsals on presurgical artificial organ models can reduce the error occurrences. However, current organ models miss multiple important features, such as a lack of tissue-mimicking properties and quantitative sensing feedback, significantly limiting their capabilities in advanced surgical planning and rehearsal. Therefore, the design and development of new methods and customized inks to fabricate patient-specific 3D-printed artificial organ models with accurate tissue-mimicking sensation and real-time operation feedback can be greatly beneficial to surgical applications and outcomes.This chapter introduces relevant fabrication, properties, characterization, and applications of 3D-printed patient-specific prostate models with physical properties of tissue and integrated soft electronic sensors.

Indexed as

Artificial OrgansPrinting, Three-DimensionalHumansMaleModels, AnatomicProstateTissue Engineering3D printingArtificial organ modelsSurgical applicationsTactile sensorsTissue-mimicking inks

Identifiers

PMID40029604

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.